Fluentd and Kafka
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This document discusses using Fluentd to collect streaming data from Apache Kafka. It presents two approaches: 1) the fluent-plugin-kafka plugin which allows Fluentd to act as a producer and consumer of Kafka topics, and 2) the kafka-fluentd-consumer project which runs a standalone Kafka consumer that sends events to Fluentd. Configuration examples are provided for both approaches. The document concludes that Fluentd and Kafka can work together to build reliable and flexible data pipelines.
Fluentd and Kafka
- 1. Fluentd and Kafka Hadoop / Spark Conference Japan 2016 Feb 8, 2016
- 2. Who are you? • Masahiro Nakagawa • github: @repeatedly • Treasure Data Inc. • Fluentd / td-agent developer • Fluentd Enterprise support • I love OSS :) • D Language, MessagePack, The organizer of several meetups, etc…
- 3. Fluentd • Pluggable streaming event collector • Lightweight, robust and flexible • Lots of plugins on rubygems • Used by AWS, GCP, MS and more companies • Resources • http://www.fluentd.org/ • Webinar: https://www.youtube.com/watch?v=6uPB_M7cbYk
- 4. Popular case App Push Push Forwarder Aggregator Destination
- 5. • Distributed messaging system • Producer - Broker - Consumer pattern • Pull model, replication, etc Apache Kafka App Push Pull Producer Broker DestinationConsumer
- 6. Push vs Pull • Push: • Easy to transfer data to multiple destinations • Hard to control stream ratio in multiple streams • Pull: • Easy to control stream flow / ratio • Should manage consumers correctly
- 7. There are 2 ways • fluent-plugin-kafka • kafka-fluentd-consumer
- 8. fluent-plugin-kafka • Input / Output plugin for kafka • https://github.com/htgc/fluent-plugin-kafka • in_kafka, in_kafka_group, out_kafka, out_kafka_buffered • Pros • Easy to use and output support • Cons • Performance is not primary
- 9. Configuration example <source> @type kafka topics web,system format json add_prefix kafka. # more options </source> <match kafka.**> @type kafka_buffered output_data_type msgpack default_topic metrics compression_codec gzip required_acks 1 </match> https://github.com/htgc/fluent-plugin-kafka#usage
- 10. kafka fluentd consumer • Stand-alone kafka consumer for fluentd • https://github.com/treasure-data/kafka-fluentd-consumer • Send cosumed events to fluentd’s in_forward • Pros • High performance and Java API features • Cons • Need Java runtime
- 11. Run consumer • Edit log4j and fluentd-consumer properties • Run following command: $ java -Dlog4j.configuration=file:///path/to/log4j.properties -jar path/to/kafka-fluentd-consumer-0.2.1-all.jar path/to/fluentd-consumer.properties
- 12. Properties example fluentd.tag.prefix=kafka.event. fluentd.record.format=regexp # default is json fluentd.record.pattern=(?<text>.*) # for regexp format fluentd.consumer.topics=app.* # can use Java Rege fluentd.consumer.topics.pattern=blacklist # default is whitelist fluentd.consumer.threads=5 https://github.com/treasure-data/kafka-fluentd-consumer/blob/master/config/fluentd-consumer.properties
- 13. With Fluentd example <source> @type forward </source> <source> @type exec command java - Dlog4j.configuration=file:///path/to/ log4j.properties -jar /path/to/kafka- fluentd-consumer-0.2.1-all.jar /path/ to/config/fluentd- consumer.properties tag dummy format json </source> https://github.com/treasure-data/kafka-fluentd-consumer#run-kafka-consumer-for-fluentd-via-in_exec
- 14. Conclusion • Kafka is now becomes important component on data platform • Fluentd can communicate with Kafka • Fluentd plugin and kafka consumer • Building reliable and flexible data pipeline with Fluentd and Kafka